The week's pick
Reseach Article
Analysis of Various Decision Tree Algorithms for Classification in Data Mining
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 163 - Number 8 |
| Year of Publication: 2017 |
| Authors: Bhumika Gupta, Aditya Rawat, Akshay Jain, Arpit Arora, Naresh Dhami |
10.5120/ijca2017913660
|
Bhumika Gupta, Aditya Rawat, Akshay Jain, Arpit Arora, Naresh Dhami . Analysis of Various Decision Tree Algorithms for Classification in Data Mining. International Journal of Computer Applications. 163, 8 ( Apr 2017), 15-19. DOI=10.5120/ijca2017913660
Abstract
Today the computer technology and computer network technology has developed so much and is still developing with pace.Thus, the amount of data in the information industry is getting higher day by day. This large amount of data can be helpful for analyzing and extracting useful knowledge from it. The hidden patterns of data are analyzed and then categorized into useful knowledge. This process is known as Data Mining. [4].Among the various data mining techniques, Decision Tree is also the popular one. Decision tree uses divide and conquer technique for the basic learning strategy. A decision tree is a flow chart-like structure in which each internal node represents a “test” on an attribute where each branch represents the outcome of the test and each leaf node represents a class label. This paper discusses various algorithms of the decision tree (ID3, C4.5, CART), their features, advantages, and disadvantages.
References
- Anuj Rathee and Robin Prakash Mathur, “Survey on Decision Tree Classification algorithms for the evaluation of Student Performance”,(IJCT),ISSN:2277-3061,March-April,2013.
- Badr HSSINA, Abdelkarim MERBOUHA, Hanane EZZIKOURI, Mohammed ERRITALI,“A comparative study of decision tree ID3 and C4.5”, (IJACSA).
- Devinder Kaur, Rajiv Bedi and Dr. Sunil Kumar Gupta, “Implementation of Enhanced Decision Tree Algorithm on Traffic Accident Analysis”, (IJSRT), ISSN: 2379-3686, 15th September 2015.
- G.Kesavaraj, Dr. S.Sukumaran, “A Study On Classification Techniques in Data Mining”, IEEE-31661, July 4-6, 2013.
- Han J., Kamber M., and Pei J. (2012) Data Mining: Concepts and Techniques, 3rd edition. The Morgan Kaufmann Series in Data Management Systems, Jim Gray, Series Editor.
- Hemlata Chahal, “ID3 Modification and Implementation in Data Mining”, International Journal of Computer Applications (0975-8887), Volume 80-No7, October 2013.
- Jatinder Kaur and Jasmeet Singh Gurm, “Optimizing the Accuracy of CART algorithm by Using Genetic Algorithm”, (IJST), Volume 3 Issue 4, Jul-Aug, 2015.
- M.S. Mythili and Dr. A.R.Mohamed Shanavas, “An Analysis of students’ performance using classification algorithms”, (IOSR-JCE), e-ISSN:2278-0661,p-ISSN:2278-8727, Jan. 2014.
- Qing-Yun Dai, Chun-ping Zhang and Hao Wu,“Research of Decision Tree Classification Algorithm in Data Mining”, International Journal of Database Theory and ApplicationVol.9, No.5(2016),pp.1-8.
- T.Miranda Lakshmi, A.Martin, R.Mumtaj Begum, and Dr. V.Prasanna Venkatesnan,“An Analysis on Performance of decision Tree Algorithms using Student’s Qualitative Data”, I.J. Modern Education and Computer Science, June 2013.
- (2017, March 4), C4.5[Online].Available: http://en.wikipedia.org/wiki/C4.5_algorithm.
- (2017, March 4), ID3[Online].Available: http://en.wikipedia.org/wiki/ID3_algorithm.
- (2017, March 4), Random Forest[Online].Available:http://en.wikipedia.org/wiki/Random_Forest.
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